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airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes.
This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses.
This project has 2 subprojects:
Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api
Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api
A video from the first prototype has been made:
http://www.youtube.com/watch?v=qH-IQgYy9zg
Above video shows a popperian agent collecting mining ore from 3...
This project provides a framework for testing and comparing different machine learning algorithms (particularly reinforcement learning methods) in different scenarios. Its intended area of application is in research and education.
Ensure the availability of your data with coverage across AWS, Azure, and GCP on MongoDB Atlas—the multi-cloud database for every enterprise.
MongoDB Atlas allows you to build and run modern applications across 125+ cloud regions, spanning AWS, Azure, and Google Cloud. Its multi-cloud clusters enable seamless data distribution and automated failover between cloud providers, ensuring high availability and flexibility without added complexity.
A Python class library of tools for learning agents, including reinforcement learning algorithms, function approximators, and vector quantizations algorithms. (Pronounced "plastic".)
General purpose agents using reinforcement learning. Combines radial basis functions, temporal difference learning, planning, uncertainty estimations, and curiosity. Intended to be an out-of-the-box solution for roboticists and game developers.